This paper discusses optimal controller structure design for a Synchronous Reluctance Motor (SynRM). Optimization of controller parameters is based on a new modified BAT optimization algorithm (mBAT). SynRM is represented with a nonlinear dynamic model of a synchronous machine. All gathered non-linearities of SynRM are taken into account in the controller's design and optimization procedure withmBAT. A novel SynRM controller structure with a modified robust disturbance observer (mRDO) is presented. The modified mRDO ensures a higher level of stability margin, efficient disturbance rejection, and enables transparent controller parametrization and optimization. Controller synthesis is based on robust H? pole-placement technique. The H? robust criteria are presented in the form of spectral polynomials and their strong positivity conditions. Spectral polynomials (SP) can be directly used as objective functions in the mBAT optimization procedure. The mBAT algorithm, in terms of the derived SP introduces a novel approach to adaptive weighting function selection and modification of BAT velocity in the position formula. The new modification of the BAT algorithm is inspired by feedback control theory and Lyapunov exponential stability property. The proposed modification of the mBAT significantly increasesthe efficiency of the given optimization problem.
COBISS.SI-ID: 1024306524
The design optimization of an axial flux permanent magnet synchronous machine with a coreless stator and double external rotor is accomplished by using evolutionary optimization with a genetic algorithm and an analytical evaluation of objective functions. On the basis of eight variable geometry parameters, five objective functions are optimized in order to determine the maximum volume torque density and weight torque density, the minimum volume and weight of permanent magnets per Newton-meter, and the minimum machine price per Newton-meter. Based on the geometric parameters for minimum machine price per Newton-meter, a prototype is built for the rated torque. Optimized and analytically evaluated machine characteristics are validated with a finite-element method (FEM) and the measurements of a prototype. Evolutionary optimization with the analytical evaluation of objective functions significantly shortens the computational time required for design optimization in comparison with the FEM.
COBISS.SI-ID: 84086785
This work deals with the differential evolution (DE) based method for simultaneous identification of the electric, magnetic and mechanical subsystem parameters of a line-start interior permanent magnet synchronous motor (LSIPMSM). The parameters are determined in the optimization procedure using the dynamic model of the LSIPMSM, the time behavior of voltages, currents and speed measured on the tested LSIPMSM, and the DE which is applied as the optimization tool. During the optimization procedure the DE changes the parameters of the LSIPMSM dynamic model in such a way that the differences between the measured and calculated time behavior of individual state variables is minimized. The paper focuses on the objective function definition, constraints settings for individual parameters, normalization of parameters, and above all the test and measurement procedures performed on the LSIPMSM, which all together make possible to determine the LSIPMSM dynamic model parameters valid for a broad range of operation, and thus, ensuring proper evaluation of the LSIPMSM%s line-starting capability. Some of the LSIPMSM parameters that can be determined by finite element analysis and experimental methods are compared to the values obtained by the DE, thus validating the DE based approach.
COBISS.SI-ID: 17638166
Motors in semi-hermetic compressor drives are mostly fed from line. Because of good cooling conditions, the motors are heavily loaded, and employ a specific rotor structure with ŽCŽ bore. In the field of semi-hermetic drives the use of induction motors (IMs) is still dominant, although different motor types with line-starting capabilities, as for example linestart interior permanent magnet synchronous motors (LSIPMSMs), can be used. This work presents the direct performance comparison of a family of commercially available three-phase four-pole IMs for semi-hermetic compressor drives with the equal size prototypes of LSIPMSMs. The motors were rated as 1, 2.5, 3.8, 5.5, 7.5 and 20 Hp. Presence of ŽCŽ bore in rotor structure can degrade LSIPMSM steady-state performance, therefore the LSIPMSM designs steady-state performances are evaluated by FEA as well by the experimental method. The motors' dynamic performance is experimentally evaluated as well. The ultimate goal of this study is to reveal the improvement of LSIPMSMs characteristics in comparison to IMs characteristics and to check the possibility for the immediate replacement of existent IMs with LSIPMSMs in the target semi-hermetic compressor application.
COBISS.SI-ID: 72594433
This paper presents the Extended Lindstedt-Poincare (EL-P) method with multiple time scales to treat nonstationary vibrations of the electromechanical system, which are forced by a nonideal energy source. The subject of research are two electromechanical systems consisting from rotor system with rotating disc mounted on an elastic shaft and a system with a rotating eccentric mass coupled by a nonlinear shock absorber, which are driven by a D.C. motor as a nonideal energy source. By using extended Hamilton principle, governing nonlinear differential equations of the system are derived. By using multiple time scales, which correspond to the nonlinear frequencies of the system in addition to the slow time scale, which corresponds to the slowly varying parameter, the system of partial differential equations is obtained, which is successively solved by using the proposed EL-P method. The results of computation of the nonstationary vibrations in the passage through fundamental resonance in both systems are presented.
COBISS.SI-ID: 13234454
Convection of a magnetic fluid within a perspex container was investigated experimentally and complemented by a computational Finite-Element model built according to the same physical specification. The enclosure was heated at two opposite side walls and exposed to a magnetic field provided by a Neodymium-Iron-Boron permanent magnet placed either above or below the container. The spatial temperature distribution on the front side wall of the container was recorded via infrared thermography and compared to computational results that reproduced the spatial temperature fields. The results show a significant e_ect on heat transfer by the location of the permanent magnet and gave evidence that the Kelvin body force is much stronger than buoyancy. As both body forces are temperature sensitive an increase in temperature di_erence increased both buoyancy and Kelvin body force however with a di_erent intensity that was explained via Curie’s Law and expressed as a temperature dependant magnetisation through the pyromagnetic coe_cient, K. The heat transfer was characterised by the Nusselt number and a suitable modified Rayleigh number that took the orientation of both buoyancy and Kelvin body force in account. The degree of heat transfer enhancement reported varied between a 23% reduction to a 20% enhancement.
COBISS.SI-ID: 21645078
The incorporation of magnetic barium hexaferrite nanoparticles in a transparent polymer matrix of poly (methyl methacrylate) (PMMA) is reported for the first time. The barium hexaferrite nanoplatelets doped with Sc3+, i.e., BaSc0.5Fe11.5O12 (BaHF), having diameters in the range 20 to 130 nm and thicknesses of approximately 5 nm, are synthesized hydrothermally and stabilized in 1-butanol with dodecylbenzenesulfonic acid. This method enables the preparation of monolithic nanocomposites by admixing the BaHF suspension into a liquid monomer, followed by insitu, bulk free-radical polymerization. The PMMA retains its transparency for loadings of BaHF nanoparticles up to 0.27 wt.%, meaning that magnetically and optically anisotropic, monolithic nanocomposites can be synthesized when the polymerization is carried out in a magnetic field. The excellent dispersion of the magnetic nanoparticles, coupled with a reasonable control over the magnetic properties achieved in this investigation, is encouraging for the magneto-optical applications of these materials.
COBISS.SI-ID: 18777878
Magnetic particles with a controlled Curie temperature were prepared by reducing a Ni,Cu-hydrazine complex that was synthesized in a compartmentalizedstate of reverse micelles. The planned Curie temperature of 43 °C was achieved by a thermally activated homogenization of as-prepared alloy particles embedded in a NaCl salt environment. The particles were superparamagnetic with a blocking temperature of 16.5 K and a room-temperaturemagnetization of 2.5 emu/g. The particles exhibited a therapeutic Curie temperature that is suitable for self-regulating magnetic hyperthermia.
COBISS.SI-ID: 16893718
Grounding systems are an important part of protection systems which protect people and devices in case of defects in electro energetic systems or lightning strikes. The Finite Element Method (FEM) is often used for proper dimensioning of the grounding systems. Often data about the soil in the surroundings of the grounding system are obtained using measurements. Soil parameters can be determined using analytical soil models, and the determination of the soil models’ parameters, which are based on the measured data, is an optimization problem. In this paper, different soil models are tested on different measured data and compared with each other. Different metaheuristics are used and tested for the determination of soil parameters: A Genetic Algorithm, Differential Evolution with two different strategies, Teaching-Learning Based Optimization, Artificial Bee Colony and Dynamic Optimization using Self-Adaptive Differential Evolution. Based on the test results, we improved the most appropriate method. As a result, the most appropriate soil model among those tested is selected, and a method for parameter determination is presented which combines Artificial Bee Colony and Teaching-Learning Based Optimization. The presented solution is appropriate to be used with, or as a part of, FEM calculation software.
COBISS.SI-ID: 21391894
Magnetization curves are obtained with measurements and used for the description of magnetic material properties. In the case where the curve is rough problems can appear during the Finite Element Method (FEM) calculations. One of the solutions is the use of an analytically written curve, which fits the measured curve. In this paper different analytical expressions are tested on different measured magnetization curves and compared with each other. Different evolutionary methods are used and tested for the determination of the analytical expressions’ parameters: The Genetic Algorithm, Differential Evolution with three different strategies, Teaching-Learning Based Optimization and Artificial Bee Colony. To obtain credible and optimal results, we made a statistic evaluation of the results using Cross-validation, CRS4EAs (Chess rating system for evolutionary algorithms), and the Holm test. Based on the test’s results we improved the more appropriate evolutionary method, which was Artificial Bee Colony, using the Levenberg-Marquardt algorithm. As a result, two different methods: are presented and tested which combine Artificial Bee Colony and the Levenberg-Marquardt algorithm. An analytical expression is presented which can be used for a wide range of different materials’ curves and also a stable and efficient method for the determination of the analytical expression’s parameters. The presented solution is appropriate to be used together with, or as a part of, FEM calculation software. For preparation of magnetic material data the presented solution can be used as an independent programme for the transformation of the H-B table of values presenting not-smooth measured magnetic material curves (or measured with too few points) into the H-B table of values presenting smooth magnetic material curve which can be used as input data for any FEM software.
COBISS.SI-ID: 19965462